Neural network hardware and software solutions for sorting of waste plastics for recycling
While plastic recycling efforts have expanded during the past several years, the cost of recovering plastics is still a major impediment for recyclers. Several factors contribute to the prohibitive cost of recycled resins, including the present low marketability of products made with mixed recycled materials, and costs of collecting, sorting and reprocessing plastic materials. A method for automatic sorting of post-consumer plastics into pure polymer streams is needed to overcome the inaccuracies and low product throughput of the currently used method of hand sorting of waste plastics for recycling. The Society of Plastics has designated seven categories as recyclable: Polyethylene terephthalate (PET); High Density Polyethylene (HDPE); Polyvinyl Chloride (PVC); Low Density Polyethylene (LDPE); Polypropylene (PP); Polystyrene (PS); and Other (mixtures, layered items, etc.). With these categories in mind, a system for sorting of waste plastics using near-infrared reflectance spectra and a backpropagation neural network classifier has been developed. A solution has been demonstrated in the laboratory using a high resolution, and relatively slow instrument. A faster instrument is being developed at this time. Neural network hardware options have been evaluated for use in a real-time industrial system. In the lab, a Fourier transform Near Infrared (FT-NIR) scanning spectrometer was used to gather reflectance data from various locations on samples of actual waste plastics. Neural networks were trained off-line with this data using the NeuralWorks Professional II Plus software package on a SparcStation 2. One of the successfully trained networks was used to compare the neural accelerator hardware options available. The results of running this worst case'' network on the neural network hardware will be presented. The AT T ANNA chip and the Intel 80170NX chip development system were used to determine the ease of implementation and accuracies for this network.
- Research Organization:
- Sandia National Labs., Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE; USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC04-76DP00789
- OSTI ID:
- 6349888
- Report Number(s):
- SAND-92-2903C; CONF-9305187-1; ON: DE93012850
- Resource Relation:
- Conference: Ideas in science and electronics, Albuquerque, NM (United States), 11 May 1993
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
MUNICIPAL WASTES
RECYCLING
PLASTICS
SORTING
NEURAL NETWORKS
COMPUTER CALCULATIONS
COMPUTERIZED CONTROL SYSTEMS
EXPERT SYSTEMS
FOURIER TRANSFORM SPECTROMETERS
INFRARED SPECTROMETERS
MATERIALS RECOVERY
NEAR INFRARED RADIATION
POLYESTERS
POLYETHYLENES
POLYPROPYLENE
POLYSTYRENE
PVC
WASTE PROCESSING
CHLORINATED ALIPHATIC HYDROCARBONS
CONTROL SYSTEMS
ELECTROMAGNETIC RADIATION
ESTERS
HALOGENATED ALIPHATIC HYDROCARBONS
INFRARED RADIATION
MANAGEMENT
MATERIALS
MEASURING INSTRUMENTS
ON-LINE CONTROL SYSTEMS
ON-LINE SYSTEMS
ORGANIC CHLORINE COMPOUNDS
ORGANIC COMPOUNDS
ORGANIC HALOGEN COMPOUNDS
ORGANIC POLYMERS
PETROCHEMICALS
PETROLEUM PRODUCTS
POLYMERS
POLYOLEFINS
POLYVINYLS
PROCESSING
RADIATIONS
SPECTROMETERS
SYNTHETIC MATERIALS
WASTE MANAGEMENT
WASTES
320604* - Energy Conservation
Consumption
& Utilization- Municipalities & Community Systems- Municipal Waste Management- (1980-)
990200 - Mathematics & Computers